ricursiveAI Releases Ripple-65B-Preview Language Model on Hugging Face
A new large language model named Ripple-65B-Preview developed by ricursiveAI has been shared on Hugging Face and made available on OpenRouter. The model features a scale of 65 billion parameters and comes with native tool calling capabilities. The release expands the ecosystem of large-scale open-source models with native tool-calling features, offering developers more choices for building advanced AI agents. High-parameter models like this provide stronger reasoning capabilities for complex enterprise and research workflows. Ripple-65B-Preview is served in BF16 format, preserving numerical precision for stable inference. Detailed fine-tuning methodologies, training data, and benchmark scores have not been extensively elaborated in the initial preview release.
## BACKGROUND
Hugging Face is a central platform for the AI community to share models, datasets, and machine learning applications. Large language models (LLMs) with high parameter counts, such as 65B models, require substantial computational resources to run but typically deliver superior performance on complex tasks.